Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/39605
Type: Artigo de Periódico
Title: Variable selection for multivariate classification aiming to detect individual adulterants and their blends in grape nectars
Authors: Carolina Sheng Whei Miaw
Marcelo Martins Sena
Scheilla Vitorino Carvalho de Souza
Itziar Ruisanchez
Maria Pilar Callao
Abstract: During the quality inspection control of fruit beverages, some types of adulterations can be detected, such as the addition or substitution with less expensive fruits. To determine whether grape nectars were adulterated by substitution with apple or cashew juice or by a mixture of both, a methodology based on attenuated total reflectance Fourier transform mid infrared spectroscopy (ATR-FTIR) and multivariate classification methods was proposed. Partial least squares discriminant analysis (PLS-DA) and soft independent modeling of class analogy (SIMCA) models were developed as multi-class methods (classes unadulterated, adulterated with cashew and adulterated with apple) with the full-spectra. PLS-DA presented better performance parameters than SIMCA in the classification of samples with just one adulterant, while poor results were achieved for samples with blends of two adulterants when using both classification methods. Three variable selection methods were tested in order to improve the effectiveness of the classification models: interval partial least squares (iPLS), variable importance in projection scores (VIP scores) and a genetic algorithm (GA). Variable selection methods improved the performance parameters for the SIMCA and PLS-DA methods when they were used to predict samples with only one adulterant. Only PLS-DA coupled with iPLS was able to classify samples with blends of two adulterants, providing sensitivity values between 100% and 83% at 100% specificity for the three studied classes.
Subject: Tecnologia de alimentos
Sucos
language: eng
metadata.dc.publisher.country: Brasil
Publisher: Universidade Federal de Minas Gerais
Publisher Initials: UFMG
metadata.dc.publisher.department: FAR - DEPARTAMENTO DE ALIMENTOS
ICX - DEPARTAMENTO DE QUÍMICA
Rights: Acesso Restrito
metadata.dc.identifier.doi: 10.1016/j.talanta.2018.07.078
URI: http://hdl.handle.net/1843/39605
Issue Date: 2018
metadata.dc.url.externa: http://https://www.sciencedirect.com/science/article/pii/S0039914018307859
metadata.dc.relation.ispartof: Talanta
Appears in Collections:Artigo de Periódico

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